Improved ADMM-based algorithms for multi-group multicasting in large-scale antenna systems with extension to hybrid beamforming

2019-10-01
Demir, Özlem Tuğfe
Tuncer, Temel Engin
In this paper, multi-group multicast beamforming is considered for the full digital and hybrid beamforming. The wireless system comprises of a multiple-antenna base station and single-antenna users. Quality-of-service (QoS)-aware design is investigated where the optimization objective is to minimize the total transmitted power subject to the signal-to-interference-plus-noise ratio (SINR) constraint at each user. In addition to the SINR constraints, per-antenna power constraint is included for each antenna of the base station. The original optimization problem for full digital beamforming is transformed into an equivalent form such that the alternating direction method of multipliers (ADMM) can be applied in an effective and computationally inexpensive manner for the large-scale antenna systems. In this new formulation, the beamformer weight vectors are decomposed into two subspaces in order to decrease the number of dual variables and multiplications. The optimum update equations are obtained for the proposed ADMM algorithm. This new reformulation is used for two different hybrid beamforming structures employing phase shifters and vector modulators. Optimum updates are derived for each system. The proposed algorithms decrease computational complexity of the existing ADMM algorithms due to the effective reformulation as well as the direct solution of the nonconvex problem. In the simulation results, it is shown that the proposed methods have better convergence behavior and less computational time than the benchmark algorithms. Furthermore, the proposed method for hybrid beamforming with vector modulators performs better than its counterpart in the literature in terms of transmitted power.
Digital Signal Processing: A Review Journal

Suggestions

New initialization methods for discrete coefficient FIR filter design with coefficient scaling and the use of scale factor in the design process
Çiloğlu, Tolga (Institute of Electrical and Electronics Engineers (IEEE), 2006-02-01)
The initialization of filter coefficients in discrete-coefficient finite-impulse-response (FIR) filter design (with coefficient scaling) using coefficient-value-assignment-based optimization techniques is considered. A common weakness of existing initialization measures, a total-square-error (TSE) measure and a maximum-error (ME) measure, is described. New TSE and ME measures that overcome the weakness are introduced. As opposed to the current knowledge, it is revealed that TSE and ME measures do not necess...
A General Framework for Optimum Iterative Blockwise Equalization of Single Carrier MIMO Systems and Asymptotic Performance Analysis
Güvensen, Gökhan Muzaffer; Yılmaz, Ali Özgür (Institute of Electrical and Electronics Engineers (IEEE), 2013-02-01)
The paper proposes a general framework for both time-domain (TD) and frequency-domain (FD) iterative blockwise equalization in single carrier (SC) wideband multiple-input multiple-output (MIMO) channels. First, a novel turbo blockwise operating equalizer structure is proposed by jointly optimizing the feed-forward and feedback filters at each iteration based on the minimum mean squared error (MMSE) criterion. Optimization of the filter coefficients, utilized for feed-forward equalization and decision feedba...
Extended Target Tracking Using Polynomials With Applications to Road-Map Estimation
Lundquist, Christian; Orguner, Umut; Gustafsson, Fredrik (Institute of Electrical and Electronics Engineers (IEEE), 2011-01-01)
This paper presents an extended target tracking framework which uses polynomials in order to model extended objects in the scene of interest from imagery sensor data. State-space models are proposed for the extended objects which enables the use of Kalman filters in tracking. Different methodologies of designing measurement equations are investigated. A general target tracking algorithm that utilizes a specific data association method for the extended targets is presented. The overall algorithm must always ...
On the Eigenstructure of DFT Matrices
Candan, Çağatay (Institute of Electrical and Electronics Engineers (IEEE), 2011-03-01)
The discrete Fourier transform (DFT) not only enables fast implementation of the discrete convolution operation, which is critical for the efficient processing of analog signals through digital means, but it also represents a rich and beautiful analytical structure that is interesting on its own. A typical senior-level digital signal processing (DSP) course involves a fairly detailed treatment of DFT and a list of related topics, such as circular shift, correlation, convolution operations, and the connectio...
Fully Integrated Autonomous Interface With Maximum Power Point Tracking for Energy Harvesting TEGs With High Power Capacity
Tabrizi, Hamed Osouli; Jayaweera, Herath M. P. C.; Muhtaroglu, Ali (Institute of Electrical and Electronics Engineers (IEEE), 2020-05-01)
In this article, a novel fully autonomous and integrated power management interface circuit is introduced for energy harvesting using thermoelectric generators (TEGs) to supply power to Internet of Thing nodes. The circuit consists of a self-starting dc & x2013;dc converter based on a dual-phase charge pump with LC-tank oscillator, a digital MPPT unit, and a 1-V LDO regulator. The novel maximum power point tracking (MPPT) algorithm avoids open-circuit state, and accommodates varying input power and ultra-lo...
Citation Formats
Ö. T. Demir and T. E. Tuncer, “Improved ADMM-based algorithms for multi-group multicasting in large-scale antenna systems with extension to hybrid beamforming,” Digital Signal Processing: A Review Journal, pp. 43–57, 2019, Accessed: 00, 2020. [Online]. Available: https://hdl.handle.net/11511/40391.